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Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

ABSTRACT: To explore the integration of imaging and molecular data for response prediction to chemoradiotherapy (CRT) for rectal cancer.Eighty-five rectal cancer patients underwent preoperative CRT. 18F-FDG PET/CT and diffusion-weighted imaging (DWI) were acquired before (TP1) and during CRT (TP2) and prior to surgery (TP3). Inflammatory cytokines and gene expression were analysed. Tumour response was defined as ypT0-1N0. Multivariate models were built combining the obtained parameters. Final models were calculated on the data combination with the highest AUC.Twenty-two patients (26%) achieved ypT0-1N0 response. 18F-FDG PET/CT had worse predictive performance than DWI and T2-volumetry (AUC 0.61±0.04, 0.72±0.03, and 0.72±0.02, respectively). Combining all imaging parameters increased the AUC to 0.81±0.03. Adding cytokines or gene expression did not improve the AUC (AUC of 0.72±0.06 and 0.79±0.04 respectively). Final models combining 18F-FDG PET/CT, DWI, and T2-weighted volumetry at all TPs and using only TP1 and TP3, allowed ypT0-1N0 prediction with a 75% sensitivity, 94% specificity and PPV of 80%.Combining 18F-FDG PET/CT, DWI, and T2-weighted MRI volumetry obtained before CRT and prior to surgery may help physicians in selecting rectal cancer patients for organ-preservation.

SUBMITTER: Joye I

PROVIDER: S-EPMC5641595 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

Joye Ines I Debucquoy Annelies A Deroose Christophe M CM Vandecaveye Vincent V Cutsem Eric Van EV Wolthuis Albert A D'Hoore André A Sagaert Xavier X Zhou Mu M Gevaert Olivier O Haustermans Karin K

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 20170621 1

<h4>Background and purpose</h4>To explore the integration of imaging and molecular data for response prediction to chemoradiotherapy (CRT) for rectal cancer.<h4>Material and methods</h4>Eighty-five rectal cancer patients underwent preoperative CRT. <sup>18</sup>F-FDG PET/CT and diffusion-weighted imaging (DWI) were acquired before (TP1) and during CRT (TP2) and prior to surgery (TP3). Inflammatory cytokines and gene expression were analysed. Tumour response was defined as ypT0-1N0. Multivariate ...[more]

PMID: 28647399

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Project description:Background: Validated markers to predict outcome in rectal cancer patients treated with multimodal therapy remain elusive. Identifying molecular profiles for disease prognosis would be required for the design of clinical trials aimed at optimizing risk-adapted therapies. We have therefore used whole genome expression profiling of tumors of a large cohort of patients enrolled in the multicenter trials of the German Rectal Cancer Study Group (GRCSG) to identify molecular profiles for individualized therapy. Methods: We prospectively collected pretherapeutic biopsies from patients (n=300) treated according to the GRCSG trial guidelines from seven different German surgical departments using rigid quality controls. These samples were profiled by global gene expression analysis and a classifier developed to predict postoperative lymph node status and Disease Free Survival (DFS). The performance of the classifier was validated with an independent, prospectively collected set of samples. Findings: The final training and test set included 198 patients. Analyzes for postoperative nodal status and DFS revealed 69 and 674 differentially regulated genes, respectively. Depending on the classifier the accuracy to predict lymph node status ranged from 64% to 69% with negative predictive values between 72% and 74%. Stratification according to DFS resulted in a good (n=99), bad (n=96) and a small very bad prognosis group (n=3). Based on linear discriminant analysis the classifier for positive lymph node status was validated in 47 independent patients and revealed an accuracy of 72% and a positive predictive value of 100%. Thereby, prediction based on molecular profiling is superior to prediction based on conventional clinical markers. Interpretation: Whole genome expression analysis of pretherapeutical biopsies resulted in a molecular classifier of disease prognosis. This classifier was successfully validated. The high positive predictive value for post therapeutic lymph node status allows identification of patients requiring alternative or intensified treatment protocols. These data are currently validated for their clinical applicability and should be taken as basis for future molecular driven clinical trials to develop risk-adapted treatments.

Dataset Information

Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

Publications

Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer.

Similar Datasets

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